Optimization of a condition-based duration-varying preventive maintenance policy for the stockless production system based on queueing model

Fund Project:
This work is supported by the National Natural Science Foundations of China (Grant Nos. 61401286, 61702341 and 61771319) and the Research Project of Shenzhen Technology University (Grant No. 201727)

A stockless production system is considered, in which the products are not produced until the orders are accepted. Due to this character, the duration of the preventive maintenance has an influence on the lead time. In addition, in this stockless production system, the cost of the preventive maintenance depends on its duration; if the lead time exceeds to the quoted lead time, some penalty cost should be considered; and the non-conforming products can still be sold by a discount. A condition-based duration-varying preventive maintenance policy is designed for the stockless production system, by making a tradeoff among the duration of the preventive maintenance, the time for the machine continuously producing, and the lead time of the order. According to the characters of the stockless production system with the designed preventive maintenance policy, it can be modeled by a BMAP/G/1 infinite-buffer queueing model with gated service and queue-length dependent vacation. Based on this queueing model, the stationary probability distributions of four performance measures for the stockless production system are analyzed, including, the number of the products produced in a production cycle, the number of the unfulfilled orders at arbitrary time, the time required to fulfill the tasks present at arbitrary time, and the lead time of the order accepted at arbitrary time. Moreover, based on some information of these performance measures, a profit function, which represents the average profit of the manufacture in a production cycle, is constructed to optimize the designed preventive maintenance policy according to specific conditions. Finally, given an example with the purchasers having different sensitivities to the lead time, some numerical experiments are carried out; and from the numerical experiments, some general results can be inferred for the stockless production system with the designed preventive maintenance policy.

J. Cao and W. Xie,
Stability of a two-queue cyclic polling system with BMAPs under gated service and state-dependent time-limited service disciplines, Queueing Systems, 85 (2017), 117-147.
doi: 10.1007/s11134-016-9504-z.

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A. Chelbi and N. Rezg,
Analysis of a production/inventory system with randomly failing production unit subjected to a minimum required availability level, International Journal of Production Economics, 99 (2006), 131-143.
doi: 10.1016/j.ijpe.2004.12.012.

J. Cao and W. Xie,
Stability of a two-queue cyclic polling system with BMAPs under gated service and state-dependent time-limited service disciplines, Queueing Systems, 85 (2017), 117-147.
doi: 10.1007/s11134-016-9504-z.

[12]

A. Chelbi and N. Rezg,
Analysis of a production/inventory system with randomly failing production unit subjected to a minimum required availability level, International Journal of Production Economics, 99 (2006), 131-143.
doi: 10.1016/j.ijpe.2004.12.012.

Figure 1.${{K''}_t}\left\{ {\left. {\left( {i,v} \right) \times [0,x]} \right|\left( {{i_0},{v_0}} \right)} \right\}$ for ${{i}_{0}} = 0$, provided that at time $t$$\left( t<{{T}_{1}} \right)$, a virtual customer arrives at the queue, while the server does not attend to the queue.

Figure 2.${{K''}_t}\left\{ {\left. {\left( {i,v} \right) \times [0,x]} \right|\left( {{i_0},{v_0}} \right)} \right\}$ for ${{i}_{0}}\ge 1$, provided that at time $t$$\left( t<{{T}_{1}} \right)$, a virtual customer arrives at the queue, while the server does not attend to the queue.

Figure 4.${K''_t}\left\{ {\left. {\left( {i,v} \right) \times [0,x]} \right|\left( {{i_0},{v_0}} \right)} \right\}$ for ${{i}_{0}}\ge 2$ and ${{i}_{0}}>i>0$, provided that at time $t$$\left( t<{{T}_{1}} \right)$, a virtual customer arrives at the queue, while the server is attending to the queue.

Table 1.
The correspondence between performance measures of the stockless production system and the queueing model

The stockless production system

The queueing model

The number of the products produced in a production cycle

The queue length just after the server travels to the queue

The number of the unfulfilled orders at arbitrary time

The queue length (including the customer in service) at arbitrary time

The time required to fulfill the tasks 1 present at arbitrary time

The virtual waiting time2 at arbitrary time

The lead time of the order accepted at arbitrary time

The actual waiting time3 at arbitrary time

1 The tasks contain the future or remaining machine set-up, machine close-down as well as PM (or the idle period) in the current production cycle, and the present unfulfilled orders.2 The definition of the virtual waiting time is given in Section 5.3 The definition of the actual waiting time is given in Section 6.

The queue length (including the customer in service) at arbitrary time

The time required to fulfill the tasks 1 present at arbitrary time

The virtual waiting time2 at arbitrary time

The lead time of the order accepted at arbitrary time

The actual waiting time3 at arbitrary time

1 The tasks contain the future or remaining machine set-up, machine close-down as well as PM (or the idle period) in the current production cycle, and the present unfulfilled orders.2 The definition of the virtual waiting time is given in Section 5.3 The definition of the actual waiting time is given in Section 6.